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title: Analyzing Microbial Ecology Data in R
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	<h1>Analyzing Microbial Ecology Data</h1>
	<p>I'm using these <a href="https://jkzorz.github.io/blog/"><b>tutorials</b></a> as a place to keep track of code I've used to generate R visualizations and statistical analyses, specifically for the purpose of visualizing and analyzing large microbial ecology datasets. I also talk about the analyses/visualizations here in terms of microbial amplicon/marker gene data, but these analyses can be extended for use in nearly any situation with a sample x species abundance/frequency, or sample x numerical variable type output.  
		
<p><b>Disclaimer:</b> I am in no way an R expert, which is perhaps evident in my code. However, all the code in my <a href="https://jkzorz.github.io/blog/"><b>tutorials</b></a> has worked for me in the past, and gotten me the results I wanted. There are probably hundreds of different and/or more elegant ways to obtain the same end product in R, so feel free to adapt things as needed. 
	
<p>I'm also not a statistics expert by any means, and I rely heavily on some really great resources out there. <b>My go to is <a href="https://sites.google.com/site/mb3gustame/">GUSTAME</a></b>, which is a guide to statistical analysis in microbial ecology. Also their papers: 
	<ul>
		<li><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2121141">Multivariate analyses in microbial ecology</a></li>
		<li><a href="https://www.ncbi.nlm.nih.gov/pubmed/25314312">A guide to statistical analysis in microbial ecology: a community-focused, living review of multivariate data analyses</a></li>
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